Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top

2019 | Book

Introduction to Market Research Read chapter Read first chapter

A Concise Guide to Market Research

The Process, Data, and Methods Using IBM SPSS Statistics

Authors: Prof. Dr. Marko Sarstedt, Prof. Erik Mooi

Publisher: Springer Berlin Heidelberg

Book Series : Springer Texts in Business and Economics

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Wirtschaft"

Login to get access
insite
SEARCH

About this book

This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods. It is intended for all readers who wish to know more about the market research process, data management, and the most commonly used methods in market research. The book helps readers perform analyses, interpret the results, and make sound statistical decisions using IBM SPSS Statistics. Hypothesis tests, ANOVA, regression analysis, principal component analysis, factor analysis, and cluster analysis, as well as essential descriptive statistics, are covered in detail. Highly engaging and hands-on, the book includes many practical examples, tips, and suggestions that help readers apply and interpret the data analysis methods discussed.

The new edition uses IBM SPSS version 25 and offers the following new features:

A single case and dataset used throughout the book to facilitate learningNew material on survey design and all data analysis methods to reflect the latest advances concerning each topic

Improved use of educational elements, such as learning objectives, keywords, self-assessment tests, case studies, and much more

A glossary that includes definitions of all the keywords and other descriptions of selected topics

Links to additional material and videos via the Springer Multimedia App

Table of Contents

Frontmatter
1. Introduction to Market Research
Abstract
Market research is key to understanding markets and requires the systematic gathering and interpreting of information about individuals and organizations. This will give you an essential understanding of your customers’ needs, a head start on your competitors, allow you to spot potential problems, and future growth. Drawing on real examples, we show the value of market research, describe its main purposes, and explain how market research differs from marketing research. We explain what makes, or breaks, a successful market research study and describe when market research is most needed. We also provide a description of the different types of market research providers.
Marko Sarstedt, Erik Mooi
2. The Market Research Process
Abstract
How do companies design a suitable market research plan? We explore how you can plan, start, and identify the research question that will best guide your market research. Identifying the “right” question is difficult, but we provide several strategies and suggestions to help you quickly identify and formulate a market research process. In addition, we provide a practical overview of the different types of research, including exploratory, descriptive, and causal research; the different research goals and the needs they fulfil, and discuss their different uses and potential research outcomes. We offer guidelines that will help you determine the optimal match between the research question and the type of research design.
Marko Sarstedt, Erik Mooi
3. Data
Abstract
In market research, data is critical. Testing, measuring, improving, or creating new goods and services are difficult, or even impossible, without product and customer data. We discuss the different types of data, how they are constructed, and their attributes. We subsequently discuss the advantages and disadvantages of primary and secondary data and what each type allows you to do. We show you how to assess data’s validity and reliability, and discuss the implications that measurement errors can have for your data’s quality. We conclude with a discussion of important concepts, such as population, probability and non-probability sampling, and the relevance of sample size for market research.
Marko Sarstedt, Erik Mooi
4. Getting Data
Abstract
We first address the nuts-and-bolts questions of the data collection stage. How does one find secondary data and decide on their suitability? Can one best collect primary data through, for example, observations, questionnaires, or experiments if secondary data are unavailable? We thus provide the key theoretical concepts, choices, and practicalities associated with collecting data. We first discuss the practicalities of secondary data’s use, including their sources and availability, how to assess the inclusion of key variables, and the data’s validity and reliability. If secondary data are unavailable, outdated, or too costly, we show how to best collect your own data given the question you wish to study. Primary data collection styles, such as observations, survey questionnaires, and experiments, are reviewed and we provide a range of recommendations on the type of data to use for the relevant situation, or research question.
Marko Sarstedt, Erik Mooi
5. Descriptive Statistics
Abstract
We first provide an overview of market research’s workflow. We then discuss efficient strategies to help you structure your project’s database, as well as enter, clean, and easily check the collected data for inconsistencies. In addition, we provide easy strategies that allow you to handle missing data observations before we describe the most common and useful univariate and bivariate descriptive graphs and statistics. Thereafter, we take you through the basics of SPSS and provide useful tips on how to create and interpret descriptive statistics and table outputs. A range of graphs is illustrated and applied in SPSS, including bar charts, histograms, box plots, pie charts, frequency tables, scatter graphs, crosstabs, and correlation tables, all of which are useful for differently scaled variables. We make use of a case study for an easy and meaningful interpretation of the graphs and table outputs. We conclude with recommendations for further readings and a case study with review questions.
Marko Sarstedt, Erik Mooi
6. Hypothesis Testing and ANOVA
Abstract
We first describe the essentials of hypothesis testing and how testing helps make critical business decisions of statistical and practical significance. Without using difficult mathematical formulas, we discuss the steps involved in hypothesis testing, the types of errors that may occur, and provide strategies on how to best deal with these errors. We also discuss common types of test statistics and explain how to determine which type you should use in which specific situation. We explain that the test selection depends on the testing situation, the nature of the samples, the choice of test, and the region of rejection. Drawing on a case study, we show how to link hypothesis testing logic to empirics in SPSS. The case study touches upon different test situations and helps you interpret the tables and graphics in a quick and meaningful way.
Marko Sarstedt, Erik Mooi
7. Regression Analysis
Abstract
We first provide comprehensive, but simple, access to essential regression knowledge by discussing how regression analysis works, the requirements and assumptions on which it relies, and how you can specify a regression analysis model that allows you to make critical decisions for your business, clients, or project. Each step involved in regression analysis is linked to its execution in SPSS. We show how to use a range of SPSS’s easy-to-learn statistical procedures that underlie regression analysis, which will allow you to analyze, chart, and validate regression analysis results and to assess your analysis’s robustness. Interpretation of SPSS output can be difficult, but we make this easier by means of an annotated case study. We conclude with suggestions for further readings on the use, application, and interpretation of regression analysis.
Marko Sarstedt, Erik Mooi
8. Principal Component and Factor Analysis
Abstract
We first provide comprehensive and advanced access to principal component analysis, factor analysis, and reliability analysis. Based on a discussion of the different types of factor analytic procedures (exploratory factor analysis, confirmatory factor analysis, and structural equation modeling), we introduce the steps involved in a principal component analysis and a reliability analysis, offering guidelines for executing them in SPSS. Specifically, we cover the requirements for running an analysis, modern options for extracting the factors and deciding on their number, as well as for interpreting and judging the quality of the results. Based on a step-by-step description of SPSS’s menu options, we present an in-depth discussion of each element of the SPSS output. Interpretation of output can be difficult, which we make much easier by means of various illustrations and applications, using a detailed case study to quickly make sense of the results. We conclude with suggestions for further readings on the use, application, and interpretation of factor analytic procedures.
Marko Sarstedt, Erik Mooi
9. Cluster Analysis
Abstract
We provide comprehensive and advanced knowledge of cluster analysis knowledge. We first introduce the principles of cluster analysis and outline the steps and decisions involved. We discuss how to select appropriate clustering variables and subsequently introduce modern hierarchical and partitioning methods for cluster analysis, using simple examples to illustrate how they work. We also discuss the key measures of similarity and dissimilarity, and offer guidance on how to decide the number of clusters to extract from the data. Each step in a cluster analysis is subsequently linked to its execution in SPSS, thus enabling readers to analyze, chart, and validate the results. Interpretation of SPSS output can be difficult, but we make this easier by means of an annotated case study. We conclude with suggestions for further readings on the use, application, and interpretation of cluster analysis.
Marko Sarstedt, Erik Mooi
10. Communicating the Results
Abstract
Communicating the results of your study, project, or business case is crucial in market research. We thus discuss the core elements of a written research report, provide guidelines on how to structure its core elements, and how you can communicate the research findings to your audience in terms of their characteristics and needs. We show you how to organize and simplify complex and dense information in an efficient and reader-friendly way. Using SPSS, and drawing on a case study, we show how you can combine and present several graphs and (regression) tables concisely and clearly. We also provide guidelines for oral presentations, suggestions for visual aids that facilitate the communication of difficult ideas, and ideas on how to best structure the oral presentation of results. Finally, we discuss ethical issues that may arise when communicating report findings to your client.
Marko Sarstedt, Erik Mooi
Backmatter
Metadata
Title
A Concise Guide to Market Research
Authors
Prof. Dr. Marko Sarstedt
Prof. Erik Mooi
Copyright Year
2019
Publisher
Springer Berlin Heidelberg
Electronic ISBN
978-3-662-56707-4
Print ISBN
978-3-662-56706-7
DOI
https://doi.org/10.1007/978-3-662-56707-4